Home/Compare/vigil-llm vs virtual-prompt-injection

Comparison

vigil-llm vs virtual-prompt-injection

Verdict

Pick vigil-llm when pricing: Vigil-LLM is open-source under the Apache License 2.0 and freely available to download. However, additional support or services may be offered on a paid basis depending on the context of usage.; pick virtual-prompt-injection when tags unique to virtual-prompt-injection: backdoor attack, data poisoning, instruction-tuned large language models, model behavior manipulation.

Markdown twin · vigil-llm alternatives · virtual-prompt-injection alternatives

GraphCanon updated today

vigil-llm logo

vigil-llm

deadbits/vigil-llm

489pushed Jan 31, 2024
vs
virtual-prompt-injection logo

virtual-prompt-injection

wegodev2/virtual-prompt-injection

27pushed Jul 6, 2024

Trust & integrity

Signalvigil-llmvirtual-prompt-injection
Maintenance
Dormant (891d since push)
As of today · github_public_v1
Dormant (735d since push)
As of today · github_public_v1
Provenance
Not a fork · Personal account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No lockfile
As of today · none

Tagline

vigil-llm
⚡ Vigil ⚡ Detect prompt injections, jailbreaks, and other potentially risky Large Language Model (LLM) inputs
virtual-prompt-injection
Backdooring instruction-tuned large language models using virtual prompt injection techniques.

Stars

vigil-llm
489
virtual-prompt-injection
27

Forks

vigil-llm
55
virtual-prompt-injection
1

Open issues

vigil-llm
16
virtual-prompt-injection
0

Language

vigil-llm
Python
virtual-prompt-injection
Python

Adopt for

vigil-llm
Vigil-LLM is specifically designed for detecting prompt injections and jailbreaks in LLM inputs, offering unique capabilities not found in all security tools.
virtual-prompt-injection
-

Persona

vigil-llm
-
virtual-prompt-injection
-

Runtime

vigil-llm
-
virtual-prompt-injection
-

License

vigil-llm
Apache-2.0
virtual-prompt-injection
-

Last pushed

vigil-llm
Jan 31, 2024
virtual-prompt-injection
Jul 6, 2024

Categories

vigil-llm
Evaluation & Observability, LLM Frameworks, Vector Databases
virtual-prompt-injection
Evaluation & Observability, LLM Frameworks

Trust and health

Days since push

vigil-llm
891d
virtual-prompt-injection
735d

Open issues (now)

vigil-llm
16
virtual-prompt-injection
0

Full report

vigil-llm
Trust report
virtual-prompt-injection
Trust report

Choose vigil-llm if…

  • Pricing: Vigil-LLM is open-source under the Apache License 2.0 and freely available to download. However, additional support or services may be offered on a paid basis depending on the context of usage..
  • Requirements: Min 4 GB RAM.
  • Tags unique to vigil-llm: adversarial-attacks, adversarial-machine-learning, large-language-models, llm-security.
  • Also covers Vector Databases.
  • When integrating large language models into applications that need robust protection against prompt injection attacks.

When NOT to use vigil-llm

  • If the focus of security efforts is solely on data breaches and not specifically on securing against adversarial machine learning techniques like prompt injections or jailbreaks.
  • When your environment is set up without Python or YARA v4.3.2, as these are prerequisites for using Vigil-LLM effectively.

Choose virtual-prompt-injection if…

  • Tags unique to virtual-prompt-injection: backdoor attack, data poisoning, instruction-tuned large language models, model behavior manipulation.
  • More recently updated (last pushed Jul 6, 2024).

When NOT to use virtual-prompt-injection

  • Last GitHub push was 736 days ago (dormant maintenance, Jul 6, 2024). Validate activity before betting a new project on virtual-prompt-injection.
  • Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: vigil-llm 489 · virtual-prompt-injection 27 (synced Jul 11, 2026).

Common questions

What is the difference between vigil-llm and virtual-prompt-injection?
vigil-llm: ⚡ Vigil ⚡ Detect prompt injections, jailbreaks, and other potentially risky Large Language Model (LLM) inputs. virtual-prompt-injection: Backdooring instruction-tuned large language models using virtual prompt injection techniques.. See the comparison table for live GitHub stats and shared categories.
When should I choose vigil-llm over virtual-prompt-injection?
Choose vigil-llm over virtual-prompt-injection when Pricing: Vigil-LLM is open-source under the Apache License 2.0 and freely available to download. However, additional support or services may be offered on a paid basis depending on the context of usage.; Requirements: Min 4 GB RAM; Tags unique to vigil-llm: adversarial-attacks, adversarial-machine-learning, large-language-models, llm-security; Also covers Vector Databases; When integrating large language models into applications that need robust protection against prompt injection attacks.
When should I choose virtual-prompt-injection over vigil-llm?
Choose virtual-prompt-injection over vigil-llm when Tags unique to virtual-prompt-injection: backdoor attack, data poisoning, instruction-tuned large language models, model behavior manipulation; More recently updated (last pushed Jul 6, 2024).
When should I avoid vigil-llm?
If the focus of security efforts is solely on data breaches and not specifically on securing against adversarial machine learning techniques like prompt injections or jailbreaks. When your environment is set up without Python or YARA v4.3.2, as these are prerequisites for using Vigil-LLM effectively.
When should I avoid virtual-prompt-injection?
Last GitHub push was 736 days ago (dormant maintenance, Jul 6, 2024). Validate activity before betting a new project on virtual-prompt-injection. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Is vigil-llm or virtual-prompt-injection more popular on GitHub?
vigil-llm has more GitHub stars (489 vs 27). Stars measure visibility, not whether either tool fits your constraints.
Are vigil-llm and virtual-prompt-injection open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to vigil-llm or virtual-prompt-injection?
GraphCanon lists graph-backed alternatives at vigil-llm alternatives and virtual-prompt-injection alternatives (vigil-llm markdown twin, virtual-prompt-injection markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, vigil-llm or virtual-prompt-injection?
vigil-llm: Dormant. virtual-prompt-injection: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for vigil-llm and virtual-prompt-injection?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: vigil-llm trust report; virtual-prompt-injection trust report.